Package: ppgmmga 1.3

Luca Scrucca

ppgmmga: Projection Pursuit Based on Gaussian Mixtures and Evolutionary Algorithms

Projection Pursuit (PP) algorithm for dimension reduction based on Gaussian Mixture Models (GMMs) for density estimation using Genetic Algorithms (GAs) to maximise an approximated negentropy index. For more details see Scrucca and Serafini (2019) <doi:10.1080/10618600.2019.1598871>.

Authors:Alessio Serafini [aut], Luca Scrucca [aut, cre]

ppgmmga_1.3.tar.gz
ppgmmga_1.3.tar.gz(r-4.5-noble)ppgmmga_1.3.tar.gz(r-4.4-noble)
ppgmmga_1.3.tgz(r-4.4-emscripten)ppgmmga_1.3.tgz(r-4.3-emscripten)
ppgmmga.pdf |ppgmmga.html
ppgmmga/json (API)
NEWS

# Install 'ppgmmga' in R:
install.packages('ppgmmga', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/luca-scr/ppgmmga/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

openblascpp

2.70 score 8 scripts 135 downloads 14 exports 36 dependencies

Last updated 1 years agofrom:40a15131db. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 12 2024
R-4.5-linux-x86_64NOTEDec 12 2024

Exports:EntropyGaussEntropyGMMEntropyMCEntropySOTEEntropyUTEntropyVARlogsumexpnclass.numpyplot.ppgmmgappgmmgappgmmga.optionsprint.ppgmmgaprint.summary.ppgmmgasummary.ppgmmga

Dependencies:clicodetoolscolorspacecrayonfansifarverforeachGAggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmclustmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalestibbleutf8vctrsviridisLitewithr

A quick tour of ppgmmga

Rendered fromppgmmga.Rmdusingknitr::rmarkdownon Dec 12 2024.

Last update: 2023-11-18
Started: 2018-10-14